Production AI – Evaluation, Security & Deployment (Advanced Handwritten Notes)

What you will learn

• ✓Understand production AI architecture and the complete AI lifecycle.
• ✓Evaluate AI systems using quality metrics, baselines and evaluation datasets.
• ✓Measure LLM correctness, relevance, faithfulness and response quality.
• ✓Understand LLM-as-a-Judge and evaluation methods.
• ✓Evaluate RAG retrieval quality and AI agent task performance.
• ✓Apply unit, integration, regression and end-to-end testing.
• ✓Understand release gates, experimentation and deployment approvals.
• ✓Monitor AI systems using logs, metrics, traces and dashboards.
• ✓Identify AI security threats, vulnerabilities and trust boundaries.
• ✓Understand prompt injection, data leakage and unsafe output risks.
• ✓Apply authentication, authorization, secrets management and tool permissions.
• ✓Understand API security and infrastructure protection.
• ✓Learn deployment architecture, containers and orchestration.
• ✓Optimize latency, throughput, scaling and infrastructure costs.
• ✓Understand MLOps, LLMOps, CI/CD and model versioning.
• ✓Apply canary releases, rollback and production monitoring.
• ✓Understand SLI, SLO, SLA and error budgets.
• ✓Learn incident response, disaster recovery and AI governance.
• ✓Design reliable, secure and scalable production AI systems.